Percolation on the gene regulatory network,

Giuseppe Torrisi et al J. Stat. Mech. (2020) 083501 https://doi.org/10.1088/1742-5468/aba7b0.

See this twitter thread for a short summary of what is in the paper.

This repository contins all the code to reproduce the figures of the paper. This repository requires:

• Python version 3.6 or higher
• Mathematica and wolframscript installed
• jupyter notebooks

Each folder performs a task. Inside each folder, use the following order to execute files:

1. *.wls
2. *.py
3. *ipynb

Also Section_4/macroscopic-cavity should be run first.

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Content of the repository

• lib: a folder with interal routines for python scripts

• Section 3 contains a Mathematica notebook

• Section 4 contains:

  • macroscopic-cavity: this folder compute the macroscopic cavity theory for type 1 networks.
  • pruning-aOC; percolation on synthetic network:
  • single-instance: microscopic cavity dynamics
  • knockout-cascade: single gene removal

• Section 5 contains: strongly connected component evaluation.

Extensions for bipartite graphs in networkx

This repository relies heavily on networkx. Some method for direct bipartite graph generation have been extendend. In particular:

• directed biparite random graph generation
• configurational model for directed bipartite graph

Moreover in- and out-component are computed for directed graph. Go in the lib folder to know more